Martijn Huisman

Educational inequalities in cause-specific mortality in middle-aged and older men and women in eight western European populations

BACKGROUNDnStudies of socioeconomic disparities in patterns of cause of death have been limited to single countries, middle-aged people, men, or broad cause of death groups. We assessed contribution of specific causes of death to disparities in mortality between groups with different levels of education, in men and women, middle-aged and old, in eight western European populations.nnnMETHODSnWe analysed data from longitudinal mortality studies by cause of death, between Jan 1, 1990, and Dec 31, 1997. Data were included for more than 1 million deaths in 51 million person years of observation.nnnFINDINGSnAbsolute educational inequalities in total mortality peaked at 2127 deaths per 100000 person years in men, and at 1588 deaths per 100000 person years in women aged 75 years and older. In this age-group, rate ratios were greater than 1.00 for total mortality and all specific causes of death, apart form prostate cancer in men and lung cancer in women, showing increased mortality in low versus high educational groups. In men, cardiovascular diseases accounted for 39% of the difference between low and high educational groups in total mortality, cancer for 24%, other diseases for 32%, and external causes for 5%. Among women, contributions were 60%, 11%, 30%, and 0%, respectively. The contributions of cerebrovascular disease, other cardiovascular diseases, pneumonia, and COPD strongly increased by age, whereas those of cancer and external causes declined. Although relative inequalities in total mortality were closely similar in all populations, we noted striking differences in the contribution of specific causes to these inequalities.nnnINTERPRETATIONnResearch needs to be broadened to include older populations, other diseases, and populations from different parts of Europe. Effective interventions should be developed and implemented to reduce exposure to cardiovascular risk factors in low-educational groups.

Socioeconomic inequalities in morbidity among the elderly; A European overview

There is some evidence on socioeconomic inequality in morbidity among elderly people, but this evidence remains fragmentary. This study aims to give a comprehensive overview of educational and income inequalities in morbidity among the elderly of eleven European countries. Data from the first wave of 1994 of the European Community Household Panel were used. The study population comprised a total of 14,107 men and 17,243 women, divided into three age groups: 60-69, 70-79 and 80+. Three health indicators were used: self-assessed health, cut down in daily activities due to a physical or mental problem, and long-term disability. The results indicate that socioeconomic inequalities in morbidity by education and income exist among the elderly in Europe, in all the countries in this study and all age groups, including the oldest old. Inequalities decline with age among women, but not always among men. Greece, Ireland, Italy and The Netherlands most often show large inequalities among men, and Greece, Ireland and Spain do so among women. To conclude, inequalities in morbidity decrease with age, but a substantive part persists in old age. To improve the health of elderly people it is important that the material, social and cultural resources of the elderly are improved.

Socioeconomic inequalities in mortality among elderly people in 11 European populations

Study objective: To describe mortality inequalities related to education and housing tenure in 11 European populations and to describe the age pattern of relative and absolute socioeconomic inequalities in mortality in the elderly European population. Design and Methods: Data from mortality registries linked with population census data of 11 countries and regions of Europe were acquired for the beginning of the 1990s. Indicators of socioeconomic status were educational level and housing tenure. The study determined mortality rate ratios, relative indices of inequality (RII), and mortality rate differences. The age range was 30 to 90+ years. Analyses were performed on the pooled European data, including all populations, and on the data of populations separately. Data were included from Finland, Norway, Denmark, England and Wales, Belgium, France, Austria, Switzerland, Barcelona, Madrid, and Turin. Main results: In Europe (populations pooled) relative inequalities in mortality decreased with increasing age, but persisted. Absolute educational mortality differences increased until the ages 90+. In some of the populations, relative inequalities among older women were as large as those among middle aged women. The decline of relative educational inequalities was largest in Norway (men and women) and Austria (men). Relative educational inequalities did not decrease, or hardly decreased with age in England and Wales (men), Belgium, Switzerland, Austria, and Turin (women). Conclusions: Socioeconomic inequalities in mortality among older men and women were found to persist in each country, sometimes of similar magnitude as those among the middle aged. Mortality inequalities among older populations are an important public health problem in Europe.

Socioeconomic differences in lack of recreational walking among older adults: the role of neighbourhood and individual factors

BackgroundPeople with a low socioeconomic status (SES) are more likely to be physically inactive than their higher status counterparts, however, the mechanisms underlying this socioeconomic gradient in physical inactivity remain largely unknown. Our aims were (1) to investigate socioeconomic differences in recreational walking among older adults and (2) to examine to what extent neighbourhood perceptions and individual cognitions regarding regular physical activity can explain these differences.MethodsData were obtained by a large-scale postal survey among a stratified sample of older adults (age 55–75 years) (N = 1994), residing in 147 neighbourhoods of Eindhoven and surrounding areas, in the Netherlands. Multilevel logistic regression analyses assessed associations between SES (i.e. education and income), perceptions of the social and physical neighbourhood environment, measures of individual cognitions derived from the Theory of Planned Behaviour (e.g. attitude, perceived behaviour control), and recreational walking for ≥10 minutes/week (no vs. yes).ResultsParticipants in the lowest educational group (OR 1.67 (95% CI, 1.18–2.35)) and lowest income group (OR 1.40 (95% CI, 0.98–2.01)) were more likely to report no recreational walking than their higher status counterparts. The association between SES and recreational walking attenuated when neighbourhood aesthetics was included in the model, and largely reduced when individual cognitions were added to the model (with largest effects of attitude, and intention regarding regular physical activity). The assiation between poor neighbourhood aesthetics and no recreational walking attenuated to (borderline) insignificance when individual cognitions were taken into account.ConclusionBoth neighbourhood aesthetics and individual cognitions regarding physical activity contributed to the explanation of socioeconomic differences in no recreational walking. Neighbourhood aesthetics may explain the association between SES and recreational walking largely via individual cognitions towards physical activity. Intervention and policy strategies to reduce socioeconomic differences in lack of recreational walking among older adults would be most effective if they intervene on both neighbourhood perceptions as well as individual cognitions.

Socioeconomic status and ischaemic heart disease mortality in 10 western European populations during the 1990s

Objective: To assess the association between socioeconomic status and ischaemic heart disease (IHD) mortality in 10 western European populations during the 1990s. Design: Longitudinal study. Setting: 10 European populations (95 009 822 person years). Methods: Longitudinal data on IHD mortality by educational level were obtained from registries in Finland, Norway, Denmark, England/Wales, Belgium, Switzerland, Austria, Turin (Italy), Barcelona (Spain), and Madrid (Spain). Age standardised rates and rate ratios (RRs) of IHD mortality by educational level were calculated by using Poisson regression. Results: IHD mortality was higher in those with a lower socioeconomic status than in those with a higher socioeconomic status among men aged 30–59 (RR 1.55, 95% confidence interval (CI) 1.51 to 1.60) and 60 years and over (RR 1.22, 95% CI 1.21 to 1.24), and among women aged 30–59 (RR 2.13, 95% CI 1.98 to 2.29) and 60 years and over (RR 1.36, 95% CI 1.33 to 1.38). Socioeconomic disparities in IHD mortality were larger in the Scandinavian countries and England/Wales, of moderate size in Belgium, Switzerland, and Austria, and smaller in southern European populations among men and younger women (p < 0.0001). For elderly women the north–south gradient was smaller and there was less variation between populations. No socioeconomic disparities in IHD mortality existed among elderly men in southern Europe. Conclusions: Socioeconomic disparities in IHD mortality were larger in northern than in southern European populations during the 1990s. This partly reflects the pattern of socioeconomic disparities in cardiovascular risk factors in Europe. Population wide strategies to reduce risk factor prevalence combined with interventions targeted at the lower socioeconomic groups can contribute to reduce IHD mortality in Europe.

Using relative and absolute measures for monitoring health inequalities: Experiences from cross-national analyses on maternal and child health

BackgroundAs reducing socio-economic inequalities in health is an important public health objective, monitoring of these inequalities is an important public health task. The specific inequality measure used can influence the conclusions drawn, and there is no consensus on which measure is most meaningful. The key issue raising most debate is whether to use relative or absolute inequality measures. Our paper aims to inform this debate and develop recommendations for monitoring health inequalities on the basis of empirical analyses for a broad range of developing countries.MethodsWealth-group specific data on under-5 mortality, immunisation coverage, antenatal and delivery care for 43 countries were obtained from the Demographic and Health Surveys. These data were used to describe the association between the overall level of these outcomes on the one hand, and relative and absolute poor-rich inequalities in these outcomes on the other.ResultsWe demonstrate that the values that the absolute and relative inequality measures can take are bound by mathematical ceilings. Yet, even where these ceilings do not play a role, the magnitude of inequality is correlated with the overall level of the outcome. The observed tendencies are, however, not necessities. There are countries with low mortality levels and low relative inequalities. Also absolute inequalities showed variation at most overall levels.ConclusionOur study shows that both absolute and relative inequality measures can be meaningful for monitoring inequalities, provided that the overall level of the outcome is taken into account. Suggestions are given on how to do this. In addition, our paper presents data that can be used for benchmarking of inequalities in the field of maternal and child health in low and middle-income countries.

Educational Level and Stroke Mortality A Comparison of 10 European Populations During the 1990s

Background and Purpose— Variations between countries in occupational differences in stroke mortality were observed among men during the 1980s. This study estimates the magnitude of differences in stroke mortality by educational level among men and women aged ≥30 years in 10 European populations during the 1990s. Methods— Longitudinal data from mortality registries were obtained for 10 European populations, namely Finland, Norway, Denmark, England/Wales, Belgium, Switzerland, Austria, Turin (Italy), Barcelona (Spain), and Madrid (Spain). Rate ratios (RRs) were calculated to assess the association between educational level and stroke mortality. The life table method was used to estimate the impact of stroke mortality on educational differences in life expectancy. Results— Differences in stroke mortality according to educational level were of a similar magnitude in most populations. However, larger educational differences were observed in Austria. Overall, educational differences in stroke mortality were of similar size among men (RR, 1.27; 95% CI, 1.24 to 1.30) and women (RR, 1.29; 95% CI, 1.27 to 1.32). Educational differences in stroke mortality persisted at all ages in all populations, although they generally decreased with age. Eliminating these differences would on average reduce educational differences in life expectancy by 7% among men and 14% among women. Conclusions— Educational differences in stroke mortality were observed across Europe during the 1990s. Risk factors such as hypertension and smoking may explain part of these differences in several countries. Other factors, such as socioeconomic differences in healthcare utilization and childhood socioeconomic conditions, may have contributed to educational differences in stroke mortality across Europe.

Socioeconomic status, environmental and individual factors, and sports participation

PURPOSEnTo examine the contribution of neighborhood, household, and individual factors to socioeconomic inequalities in sports participation in a multilevel design.nnnMETHODSnData were obtained by a large-scale postal survey among a stratified sample of the adult population (age 25-75 yr) of Eindhoven (the fifth-largest city of the Netherlands) and surrounding areas, residing in 213 neighborhoods (N = 4785; response rate 64.4%). Multilevel logistic regression analyses were performed with sports participation as a binary outcome (no vs yes); that is, respondents not doing any moderate- or high-intensity sports at least once a week were classified as nonparticipants.nnnRESULTSnUnfavorable perceived neighborhood factors (e.g., feeling unsafe, small social network), household factors (material and social deprivation), and individual physical activity cognitions (e.g., negative outcome expectancies, low self-efficacy) were significantly associated with doing no sports and were reported more frequently among lower socioeconomic groups. Taking these factors into account reduced the odds ratios of doing no sports among the lowest educational group by 57%, from 3.99 (95% CI, 2.99-5.31) to 2.29 (95% CI, 1.70-3.07), and among the lowest income group by 67%, from 3.02 (95% CI, 2.36-3.86) to 1.66 (95% CI, 1.22-2.27).nnnCONCLUSIONSnA combination of neighborhood, household, and individual factors can explain socioeconomic inequalities in sports participation to a large extent. Interventions and policies should focus on all three groups of factors simultaneously to yield a maximal reduction of socioeconomic inequalities in sports participation.

Education level inequalities and transportation injury mortality in the middle aged and elderly in European settings

Objective: To study the differential distribution of transportation injury mortality by educational level in nine European settings, among people older than 30 years, during the 1990s. Methods: Deaths of men and women older than 30 years from transportation injuries were studied. Rate differences and rate ratios (RR) between high and low educational level rates were obtained. Results: Among men, those of low educational level had higher death rates in all settings, a pattern that was maintained in the different settings; no inequalities were found among women. Among men, in all the settings, the RR was higher in the 30–49 age group (RR 1.46, 95% CI 1.32 to 1.61) than in the age groups 50–69 and ⩾70 years, a pattern that was maintained in the different settings. For women for all the settings together, no differences were found among educational levels in the three age groups. In the different settings, only three had a high RR in the youngest age group, Finland (RR 1.33, 95% CI 1.01 to 1.74), Belgium (RR 1.38; 95% CI 1.13 to 1.67), and Austria (RR 1.49, 95% CI 0.75 to 2.96). Conclusion: This study provides new evidence on the importance of socioeconomic inequalities in transportation injury mortality across Europe. This applies to men, but not to women. Greater attention should be placed on opportunities to select intervention strategies tailored to tackle socioeconomic inequalities in transportation injuries.

Household and food shopping environments: do they play a role in socioeconomic inequalities in fruit and vegetable consumption? A multilevel study among Dutch adults.

Background: Fruit and vegetables are protective of a number of chronic diseases; however, their intakes have been shown to vary by socioeconomic position (SEP). Household and food shopping environmental factors are thought to contribute to these differences. To determine whether household and food shopping environmental factors are associated with fruit and vegetable (FV) intakes, and contribute to socioeconomic inequalities in FV consumption. Methods: Cross-sectional data were obtained by a postal questionnaire among 4333 adults (23–85 years) living in 168 neighbourhoods in the south-eastern Netherlands. Participants agreed/disagreed with a number of statements about the characteristics of their household and food shopping environments, including access, prices and quality. Education was used to characterise socioeconomic position (SEP). Main outcome measures were whether or not participants consumed fruit or vegetables on a daily basis. Multilevel logistic regression models examined between-area variance in FV consumption and associations between characteristics of the household and food shopping environments and FV consumption. Results: Only a few household and food shopping environmental factors were significantly associated with fruit and vegetable consumption, and their prevalence was low. Participants who perceived FV to be expensive were more likely to consume them. There were significant socioeconomic inequalities in fruit and vegetable consumption (ORs of not consuming fruit and vegetables were 4.26 and 5.47 among the lowest-educated groups for fruit and vegetables, respectively); however, these were not explained by any household or food shopping environmental factors. Conclusions: Improving access to FV in the household and food shopping environments will only make a small contribution to improving population consumption levels, and may only have a limited effect in reducing socioeconomic inequalities in their consumption.